In the context of feature relevance, I am trying to understand the meaning of the correlation method for feature selection. Can somebody please explain if the following results of the correlation coefficients arise, then should I take that feature? The rule is to select the features for which corrcoeff values are greater than 0.5. Please correct me if wrong. The way I am calculating is using Matlab's corrcoeff(target,feature)
where target
and feature
are vectors
Case1: corrcoeff returns NaN values --
Nan Nan
Nan 1
Should the feature be selected since the value is greater than 0.5?
Case2: corrcoeff returns 0 values
0 0
0 1
In this case, I should reject the feature.
Case3:
-0.3 0
0 -0.3
Negatively correlated but absolute values less than 0.5, so reject the feature
Case4: What if there is no linear relationship at all in which case corrcoeff
will not work. How do I know if there is no linear relationship and in that case how to do feature selection; is there any other function or technique?